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DOE OSTI2021

Optical calibration of the SNO+ detector in the water phase with deployed sources

SNO+ is a large-scale liquid scintillator experiment with the primary goal of searching for neutrinoless double beta decay, and is located approximately 2 km underground in SNOLAB, Sudbury, Canada. The detector acquired data for two years as a pure water Cherenkov detector, starting in May 2017. During this period, the optical properties of the detector were measured in situ using a deployed light diffusing sphere, with the goal of improving the detector model and the energy response systematic uncertainties. The measured parameters included the water attenuation coefficients, effective attenuation coefficients for the acrylic vessel, and the angular response of the photomultiplier tubes and their surrounding light concentrators, all across different wavelengths. Finally, the calibrated detector model was validated using a deployed tagged gamma source, which showed a 0.6% variation in energy scale across the primary target volume.

47 OTHER INSTRUMENTATION↗

NASA NTRS2003

The NASA Airborne Earth Science Microwave Imaging Radiometer (AESMIR): A New Sensor for Earth Remote Sensing

The Airborne Earth Science Microwave Imaging Radiometer (AESMIR) is a versatile new airborne imaging radiometer recently developed by NASA. The AESMIR design is unique in that it performs dual-polarized imaging at all standard passive microwave frequency bands (6-89 GHz) using only one sensor headscanner package, providing an efficient solution for Earth remote sensing applications (snow, soil moisture/land parameters, precipitation, ocean winds, sea surface temperature, water vapor, sea ice, etc.). The microwave radiometers themselves will incorporate state-of-the-art receivers, with particular attention given to instrument calibration for the best possible accuracy and sensitivity. The single-package design of AESMIR makes it compatible with high-altitude aircraft platforms such as the NASA ER-2s. The arbitrary 2-axis gimbal can perform conical and cross-track scanning, as well as fixed-beam staring. This compatibility with high-altitude platforms coupled with the flexible scanning configuration, opens up previously unavailable science opportunities for convection/precip/cloud science and co-flying with complementary instruments, as well as providing wider swath coverage for all science applications. By designing AESMIR to be compatible with these high-altitude platforms, we are also compatible with the NASA P-3, the NASA DC-8, C-130s and ground-based deployments. Thus AESMIR can provide low-, mid-, and high- altitude microwave imaging. Parallel filter banks allow AESMIR to simultaneously simulate the exact passbands of multiple satellite radiometers: SSM/I, TMI, AMSR, Windsat, SSMI/S, and the upcoming GPM/GMI and NPOESS/CMIS instruments --a unique capability among aircraft radiometers. An L-band option is also under development, again using the same scanner. With this option, simultaneous imaging from 1.4 to 89 GHz will be feasible. And, all receivers except the sounding channels will be configured for 4-Stokes polarimetric operation using high-speed digital correlators in the near future. The capabilities and unique design features of this new sensor will be described, and example imagery will be presented.

Kim, Edward↗

NASA NTRSDate not supplied

Machine Learning Approaches for Rare-Earth Silicate Environmental Barrier Coating Thermochemical and Thermomechanical Property Predictions

Environmental barrier coatings (EBCs) are a necessary enabling technology for the transition from superalloys to silicon carbide (SiC) ceramic matrix composites (CMCs) in gas turbine engines for increased efficiency and decreased fuel costs. SiC-based CMCs are prone to oxidation-based degradation in the engine hot section, and rare-earth (RE) silicates are promising candidates for EBCs due to their close thermal expansion match to the composite substrate and oxidation resistance. However, the design of EBCs is hindered by the large chemical space of candidate materials and the difficulty in obtaining material properties for engineering optimization. This is especially difficult as research continues into mixed-cation or “high-entropy” RE silicates. First-principles computational methods such as density functional theory (DFT) are highly effective at calculating material properties to guide coating design but are limited by their computational cost. Atomistic simulations have the potential to both accelerate property calculations and expand the properties able to be calculated due to their lower computational compared to DFT. However, they require interatomic potentials (IAPs) specific to the material system of interest, and, to our knowledge, there are no suitable IAPs for RE silicates. Machine learning (ML) is a promising technique to accelerate material property predictions indirectly by generating IAPs for atomistic simulations or via direct prediction. In this work, we present two ML approaches to accelerate the calculation of RE silicate properties relevant to EBC design: 1) a ML-derived interatomic potential (IAP) for atomistic simulations of yttrium disilicate (Y2Si2O7) from DFT training data, and 2) a neural network (NN) model to directly predict thermochemical properties of RE silicates and oxides directly from easily obtainable unit cell parameters. Classical MD simulations using the IAP yield lattice properties and bond lengths in good agreement with both DFT and experimental results from x-ray diffraction. Thermodynamic properties calculated using the finite-displacement phonon method and quasi-harmonic approximation were orders of magnitude faster than DFT with good agreement to the DFT results. The IAP was also used to calculate properties such as coefficient of thermal expansion (CTE) that require large simulation supercells and are therefore difficult with DFT. The IAP correctly predicted the anisotropic nature of the CTE in three different phases of Y2Si2O7. The NN model predicts constant pressure heat capacity, Cp, orders of magnitude faster than DFT calculations, which can enable its use as a surrogate model for multiscale simulations. The two methods presented in this work demonstrate the utility of ML for accelerating the prediction of RE silicate properties, which can in turn accelerate EBC design and optimization.

machine learning↗

DOE OSTI2021

Application of spectroscopic evidence to diffuse layer model (DLM) parameter estimation for cation adsorption onto ferrihydrite in single- and bi-solute systems

The diffuse layer model (DLM) is one of the most frequently used surface complexation models (SCM) for predicting cation adsorption onto ferrihydrite. However, the DLM with its existing database sometimes fails to predict cation adsorption, especially in multi-solute systems. Notably, the failure is often attributed to inaccurate selection of the surface complexes and/or underestimation of the site density for DLM formulation. DLM simulations of batch adsorption data conducted with cadmium, copper, lead, and zinc on ferrihydrite in CO2 free systems demonstrates the ability of the DLM to fit single-solute data reasonably well but highlights its limitations with respect to predicting bi-solute data. Modifications to the DLM were made in two steps. First, spectroscopic evidence was used to guide cation complexation reactions at the ferrihydrite surface. Second, surface characteristics (reactive site density, specific surface area, and acidity constants) of ferrihydrite were updated according to recent literature. The results from this study suggest that when spectroscopic verification is employed and surface site density is increased, a simple two-site DLM can predict cation adsorption on ferrihydrite in single-solute systems for pH data above 3.5 and in most of the bi-solute systems tested.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2016

Development of a Perfectly Matched Layer Technique for a Discontinuous-Galerkin Spectral-Element Method

The numerical simulation of many aerodynamic non-periodic flows of practical interest involves discretized computational domains that often must be artificially truncated. Appropriate boundary conditions are required at these truncated domain boundaries, and ideally, these boundary conditions should be perfectly "absorbing" or "nonreflecting" so that they do not contaminate the flow field in the interior of the domain. The proper specification of these boundaries is critical to the stability, accuracy, convergence, and quality of the numerical solution, and has been the topic of considerable research. The need for accurate boundary specification has been underscored in recent years with efforts to apply higher-fidelity methods (DNS, LES) in conjunction with high-order low-dissipation numerical schemes to realistic flow configurations. One of the most popular choices for specifying these boundaries is the characteristics-based boundary condition where the linearized flow field at the boundaries are decomposed into characteristic waves using either one-dimensional Riemann or other multi-dimensional Riemann approximations. The values of incoming characteristics are then suitably modified. The incoming characteristics are specified at the in flow boundaries, and at the out flow boundaries the variation of the incoming characteristic is zeroed out to ensure no reflection. This, however, makes the problem ill-posed requiring the use of an ad-hoc parameter to allow small reflections that make the solution stable. Generally speaking, such boundary conditions work reasonably well when the characteristic flow direction is normal to the boundary, but reflects spurious energy otherwise. An alternative to the characteristic-based boundary condition is to add additional "buffer" regions to the main computational domain near the artificial boundaries, and solve a different set of equations in the buffer region in order to minimize acoustic reflections. One approach that has been used involves modeling the pressure fluctuations as acoustic waves propagating in the far-field relative to a single noise-source inside the buffer region. This approach treats vorticity-induced pressure fluctuations the same as acoustic waves. Another popular approach, often referred to as the "sponge layer," attempts to dampen the flow perturbations by introducing artificial dissipation in the buffer region. Although the artificial dissipation removes all perturbations inside the sponge layer, incoming waves are still reflected from the interface boundary between the computational domain and the sponge layer. The effect of these refkections can be somewhat mitigated by appropriately selecting the artificial dissipation strength and the extent of the sponge layer. One of the most promising variants on the buffer region approach is the Perfectly Matched Layer (PML) technique. The PML technique mitigates spurious reflections from boundaries and interfaces by dampening the perturbation modes inside the buffer region such that their eigenfunctions remain unchanged. The technique was first developed by Berenger for application to problems involving electromagnetic wave propagation. It was later extended to the linearized Euler, Euler and Navier-Stokes equations by Hu and his coauthors. The PML technique ensures the no-reflection property for all waves, irrespective of incidence angle, wavelength, and propagation direction. Although the technique requires the solution of a set of auxiliary equations, the computational overhead is easily justified since it allows smaller domain sizes and can provide better accuracy, stability, and convergence of the numerical solution. In this paper, the PML technique is developed in the context of a high-order spectral-element Discontinuous Galerkin (DG) method. The technique is compared to other approaches to treating the in flow and out flow boundary, such as those based on using characteristic boundary conditions and sponge layers. The superiority of the current PML technique over other approaches is demonstrated for a range of test cases, viz., acoustic pulse propagation, convective vortex, shear layer flow, and low-pressure turbine cascade flow. The paper is structured as follows. We first derive the PML equations from the non{linear Euler equations. A short description of the higher-order DG method used is then described. Preliminary results for the four test cases considered are then presented and discussed. Details regarding current work that will be included in the final paper are also provided.

Spectral↗

NASA NTRS1998

The NASA Low-Pressure Turbine Flow Physics Program

An overview of the NASA Lewis Low-Pressure Turbine (LPT) Flow Physics Program will be presented. The program was established in response to the aero-engine industry's need for improved LPT efficiency and designs. Modern jet engines have four to seven LPT stages, significantly contributing to engine weight. In addition, there is a significant efficiency degradation between takeoff and cruise conditions, of up to 2 points. Reducing the weight and part count of the LPT and minimizing the efficiency degradation will translate into fuel savings. Accurate prediction methods of LPT flows and losses are needed to accomplish those improvements. The flow in LPT passages is at low Reynolds number, and is dominated by interplay of three basic mechanisms: transition, separation and wake interaction. The affecting parameters traditionally considered are Reynolds number, freestream turbulence intensity, wake frequency parameter, and the pressure distribution (loading). Three-dimensional effects and additional parameters, particularly turbulence characteristics like length scales, spectra and other statistics, as well as wake turbulence intensity and properties also play a role. The flow of most interest is on the suction surface, where large losses are generated as the flow tends to separate at the low Reynolds numbers. Ignoring wakes, a common flow scenario, there is laminar separation, followed by transition on the separation bubble and turbulent reattachment. If transition starts earlier the separation will be eliminated and the boundary layer will be attached leading to the well known bypass transition issues. In contrast, transition over a separation bubble is closer to free shear layer transition and was not investigated as well, particularly in the turbine environment. Unsteadiness created by wakes complicates the picture. Wakes induce earlier transition, and the calmed regions trailing the induced turbulent spots can delay or eliminate separation via shear stress modification. Three-dimensional flow physics and geometry will have strong effects. Altogether a very complex and challenging problem emerges. The objective of the program is to provide improved models and physical understanding of the complex flow, which are essential for accurate prediction of flow and losses in the LPT. Experimental, computational and analytical work as complementing and augmenting approaches are used. The program involves industry, universities and research institutes, and other government laboratories. It is characterized by strong interaction among participants, quick dissemination of results, and responsiveness to industry's needs. The presentation will describe the work elements. Highlighting some activities in progress are experiments on simulated blade suction surface in low-speed wind tunnels, on curved wall, and on a flat-plate, both with pressure gradient. In the area of computation, assessment of existing models is performed using RANS (Reynolds Averaged Navier Stokes) simulations. Laminar flow DNS was completed. Analytical studies of instability and receptivity in attached and separated flows were started. In the near future the program is moving to include wake effects and development of improved modeling. Experimental work in preparation stages are: (1) Addition of wakes to the curved tunnel experiment; (2) Low-speed rotating rig experiment on GE90 engine LPT; and (3) Transonic cascade. In the area of computation, it is expected to move from model assessment towards development of improved models. In addition, a new project of Large Eddy Simulation (LES) of LPT is to begin and will provide numerical data bases. It is planned to implement the emerging improved models in a multistage turbomachinery code and to validate against the GE90 engine LPT.

Ashpis, David E.↗

NASA NTRS2013

Molecular-Based Optical Measurement Techniques for Transition and Turbulence in High-Speed Flow

High-speed laminar-to-turbulent transition and turbulence affect the control of flight vehicles, the heat transfer rate to a flight vehicle's surface, the material selected to protect such vehicles from high heating loads, the ultimate weight of a flight vehicle due to the presence of thermal protection systems, the efficiency of fuel-air mixing processes in high-speed combustion applications, etc. Gaining a fundamental understanding of the physical mechanisms involved in the transition process will lead to the development of predictive capabilities that can identify transition location and its impact on parameters like surface heating. Currently, there is no general theory that can completely describe the transition-to-turbulence process. However, transition research has led to the identification of the predominant pathways by which this process occurs. For a truly physics-based model of transition to be developed, the individual stages in the paths leading to the onset of fully turbulent flow must be well understood. This requires that each pathway be computationally modeled and experimentally characterized and validated. This may also lead to the discovery of new physical pathways. This document is intended to describe molecular based measurement techniques that have been developed, addressing the needs of the high-speed transition-to-turbulence and high-speed turbulence research fields. In particular, we focus on techniques that have either been used to study high speed transition and turbulence or techniques that show promise for studying these flows. This review is not exhaustive. In addition to the probe-based techniques described in the previous paragraph, several other classes of measurement techniques that are, or could be, used to study high speed transition and turbulence are excluded from this manuscript. For example, surface measurement techniques such as pressure and temperature paint, phosphor thermography, skin friction measurements and photogrammetry (for model attitude and deformation measurement) are excluded to limit the scope of this report. Other physical probes such as heat flux gauges, total temperature probes are also excluded. We further exclude measurement techniques that require particle seeding though particle based methods may still be useful in many high speed flow applications. This manuscript details some of the more widely used molecular-based measurement techniques for studying transition and turbulence: laser-induced fluorescence (LIF), Rayleigh and Raman Scattering and coherent anti-Stokes Raman scattering (CARS). These techniques are emphasized, in part, because of the prior experience of the authors. Additional molecular based techniques are described, albeit in less detail. Where possible, an effort is made to compare the relative advantages and disadvantages of the various measurement techniques, although these comparisons can be subjective views of the authors. Finally, the manuscript concludes by evaluating the different measurement techniques in view of the precision requirements described in this chapter. Additional requirements and considerations are discussed to assist with choosing an optical measurement technique for a given application.

Bathel, Brett F.↗

DOE OSTI2021

Search for signatures of sterile neutrinos with Double Chooz

We present a search for signatures of neutrino mixing of electron anti-neutrinos with additional hypothetical sterile neutrino flavors using the Double Chooz experiment. The search is based on data from 5 years of operation of Double Chooz, including 2 years in the two-detector configuration. The analysis is based on a profile likelihood, i.e. comparing the data to the model prediction of disappearance in a data-to-data comparison of the two respective detectors. The analysis is optimized for a model of three active and one sterile neutrino. It is sensitive in the typical mass range ${5 \times 10^{-3}}\,\mathrm{eV}^2 \lesssim \varDelta m^2_{41} \lesssim {3 \times 10^{-1}}\,\mathrm{eV}^2$ for mixing angles down to $\sin ^2 2\theta _{14} \gtrsim {0.02}$. No significant disappearance additionally to the conventional disappearance related to $\theta _{13}$ is observed and correspondingly exclusion bounds on the sterile mixing parameter $\theta _{14}$ as a function of $\varDelta m^2_{41}$ are obtained.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS2002

Aeroelastic Calculations of Quiet High- Speed Fan Performed

An advanced high-speed fan was recently designed under a cooperative effort between the NASA Glenn Research Center and Honeywell Engines & Systems. The principal design goals were to improve performance and to reduce fan noise at takeoff. Scale models of the Quiet High-Speed Fan were tested for operability, performance, and acoustics. During testing, the fan showed significantly improved noise characteristics, but a self-excited aeroelastic vibration known as flutter was encountered in the operating range. Flutter calculations were carried out for the Quiet High-Speed Fan using a three-dimensional, unsteady aerodynamic, Reynolds-averaged Navier-Stokes turbomachinery code named "TURBO." The TURBO code can accurately model the viscous flow effects that can play an important role in various aeroelastic problems such as flutter with flow separation, flutter at high loading conditions near the stall line (stall flutter), and flutter in the presence of shock and boundary-layer interaction. Initially, calculations were performed with no blade vibrations. These calculations were at a constant rotational speed and a varying mass flow rate. The mass flow rate was varied by changing the backpressure at the exit boundary of the computational domain. These initial steady calculations were followed by aeroelastic calculations in which the blades were prescribed to vibrate harmonically in a natural mode, at a natural frequency, and with a fixed interblade phase angle between adjacent blades. The AE-prep preprocessor was used to interpolate the in-vacuum mode shapes from the structural dynamics mesh onto the computational fluid dynamics mesh and to smoothly propagate the grid deformations from the blade surface to the interior points of the grid. The aeroelastic calculations provided the unsteady aerodynamic forces on the blade surface due to blade vibrations. These forces were vector multiplied with the structural dynamic mode shape to calculate the work done on the blade during one vibration period, then this result was converted to an aerodynamic damping. Flutter occurs when the aerodynamic damping becomes negative, if structural damping is ignored. The results of these aeroelastic calculations are summarized in this plot of aerodynamic damping versus mass flow rate at a constant rotational speed. As the backpressure is increased, the mass flow rate through the fan decreases and the fan operating point moves towards the stall line. The aeroelastic calculations showed that the aerodynamic damping decreases as the stall line is approached, as observed during testing. In addition, the aeroelastic calculations with the TURBO code correctly predicted the aeroelastic parameters: the most unstable vibration mode and interblade phase angle, as observed during testing. The Quiet High-Speed Fan demonstrated significant noise reductions during testing, but flutter imposed limits on its operating range. The accurate calculation of the aeroelastic characteristics using the TURBO code is a significant step toward eliminating flutter from the operating range and toward realizing the benefits of reduced fan noise. The aeroelastic calculations described here were performed under a grant by University of Toledo researchers in collaboration with Glenn's researchers.

Bakhle, Milind A.↗

NASA NTRS2017

Stabilization of Hypersonic Boundary Layers by Linear and Nonlinear Optimal Perturbations

The effect of stationary, finite-amplitude, linear and nonlinear optimal perturbations on the modal disturbance growth in a Mach 6 axisymmetric flow over a 7 deg. half-angle cone with 0:126 mm nose radius and 0:305 m length is investigated. The freestream parameters (M = 6, Re(exp 1) = 18 x 10(exp. 6) /m) are selected to match the flow conditions of a previous experiment in the VKI H3 hypersonic tunnel. Plane-marching parabolized stability equations are used in conjunction with a partial-differential equation based planar eigenvalue analysis to characterize the boundary layer instability in the presence of azimuthally periodic streaks. The streaks are observed to stabilize nominally planar Mack mode instabilities, although oblique Mack mode and first-mode disturbances are destabilized. Experimentally measured transition onset in the absence of any streaks correlates with an amplification factor of N = 6 for the planar Mack modes. For high enough streak amplitudes, the transition threshold of N = 6 is not reached by the Mack mode instabilities within the length of the cone; however, subharmonic first-mode instabilities, which are destabilized by the presence of the streaks, do reach N = 6 near the end of the cone. The highest stabilization is observed at streak amplitudes of approximately 20 percent of the freestream velocity. Because the use of initial disturbance profiles based on linear optimal growth theory may yield suboptimal control in the context of nonlinear streaks, the computational predictions are extended to nonlinear optimal growth theory. Results show that by using nonlinearly optimal perturbation leads to slightly enhanced stabilization of plane Mack mode disturbances as well as reduced destabilization of subharmonic first-mode disturbances.

Incompressible boundary layer↗

NASA NTRS2021

Transition Analysis for Isolated Trips on BOLT-II Wind-Tunnel and Flight Configuration

The BOLT-II configuration designed for an upcoming flight experiment exemplifies the complexities of hypersonic boundary layer transition in the presence of multiple and potentially interacting instability mechanisms. The present paper is related to the NASA-led roughness experiment on the secondary side of the BOLT-II configuration. First, computations are performed to aid mean-flow based correlations for the transition measurements acquired during an experimental campaign in the Ludwieg Tube facility at the United States Air Force Academy. To that end, both laminar and turbulent flow computations are performed for selected conditions of the experiment with a 1:3 scale model of the slightly shorter BOLT configuration. The variation in well-known correlation parameters for transition due to isolated roughness elements with respect to element position, height, and flow Reynolds number is delineated. Furthermore, the wake instability theory is used to examine the amplification of unstable disturbances behind the centerline trip at the design conditions of the BOLT-II flight experiment and for its dynamically scaled version on the 1:3 scale model of the wind tunnel experiment. To our knowledge, this study represents the first analysis of the wake instabilities in the presence of a prominent entropy layer outside the boundary layer. At the nominal flight design condition of Re ∞ ) = 5.44 and Re ∞ = 2.5 x 10 6 /m, a diamond planform (“pizza-box”) trip with k/δ = 0.70 and planform-halfwidth-to-height ratio of b/k = 3.0 at X/L = 0.254 induces a strong distortion of the boundary-layer flow in the vicinity of the symmetry plane, such that the wake structure includes a centerline streak produced by the flow retardation behind the trip along with multiple additional, prominent vorticity structures representing the necklace vortex system. Stability results reveal that each of these streaks can support a strong amplification of wake instabilities within a frequency band of 95 kHz–255 kHz, with a peak N-factor of greater than 15 beyond X/L ≈ 0.42. The dynamically scaled wind tunnel configuration with Re ∞ = 20.25 x 10 6 /m is also found to support N > 15 at similar axial stations.

BOLT↗

NASA NTRS2022

Linear Disturbance Amplification Over Blunted Flat Plates in High-Speed Flows

Modal and nonmodal instability characteristics of cylindrically blunted flat plates with varying leading edge radii are described for Mach 4 and Mach 6 freestream conditions. The selection of leading edge radii and freestream parameters is informed by experimental conditions. The investigation of this 2D problem provides a slow entropy layer swallowing which allows for an isolated development of perturbations seeded upstream within different wall-normal regions of the flow. At both Mach numbers, a decrease in modal instability amplification was seen as the leading edge radius was increased. Nonmodal analysis reveals amplifying perturbations in the boundary layer as well as in the entropy layer. The medium bluntness regime exhibits the strongest amplification of nonmodal disturbances that is nonmonotonic in character. Small amplitude boundary forcing at the plate surface or volumetric forcing at various wall-normal heights was used to account for receptivity effects. While wall forcing effectively induced modal instabilities, only an actuation above the boundary layer captured disturbances that amplify within the entropy layer. The optimal nonmodal theory’s entropy-layer disturbance evolution exhibited outstanding agreement with controlled forcing, including receptivity effects. The evolution of entropy-layer disturbances from the optimal nonmodal theory showed excellent agreement with the results of receptivity to controlled forcing. Therefore, the nonmodal optimal growth analysis may provide a useful as well as efficient technique to identify the complete disturbance spectrum in blunt hypersonic configurations, where both modal and nonmodal disturbances can amplify in the boundary-layer and entropy-layer regions.

Boundary layer transition↗

DOE OSTI2020

NSFnets (Navier-Stokes flow nets): Physics-informed neural networks for the incompressible Navier-Stokes equations

In the last 50 years there has been a tremendous progress in solving numerically the Navier-Stokes equations using finite differences, finite elements, spectral, and even meshless methods. Yet, in many real cases, we still cannot incorporate seamlessly (multi-fidelity) data into existing algorithms, and for industrial-complexity applications the mesh generation is time consuming and still an art. Moreover, solving ill-posed problems (e.g., lacking boundary conditions) or inverse problems is often prohibitively expensive and requires different formulations and new computer codes. Here, we employ physics-informed neural networks (PINNs), encoding the governing equations directly into the deep neural network via automatic differentiation, to overcome some of the aforementioned limitations for simulating incompressible laminar and turbulent flows. We develop the Navier-Stokes flow nets (NSFnets) by considering two different mathematical formulations of the Navier-Stokes equations: the velocity-pressure (VP) formulation and the vorticity-velocity (VV) formulation. Since this is a new approach, we first select some standard benchmark problems to assess the accuracy, convergence rate, computational cost and flexibility of NSFnets; analytical solutions and direct numerical simulation (DNS) databases provide proper initial and boundary conditions for the NSFnet simulations. The spatial and temporal coordinates are the inputs of the NSFnets, while the instantaneous velocity and pressure fields are the outputs for the VP-NSFnet, and the instantaneous velocity and vorticity fields are the outputs for the VV-NSFnet. This is unsupervised learning and, hence, no labeled data are required beyond boundary and initial conditions and the fluid properties. The residuals of the VP or VV governing equations, together with the initial and boundary conditions, are embedded into the loss function of the NSFnets. No data is provided for the pressure to the VP-NSFnet, which is a hidden state and is obtained via the incompressibility constraint without extra computational cost. Unlike the traditional numerical methods, NSFnets inherit the properties of neural networks (NNs), hence the total error is composed of the approximation, the optimization, and the generalization errors. Here, we empirically attempt to quantify these errors by varying the sampling (“residual”) points, the iterative solvers, and the size of the NN architecture. For the laminar flow solutions, we show that both the VP and the VV formulations are comparable in accuracy but their best performance corresponds to different NN architectures. The initial convergence rate is fast but the error eventually saturates to a plateau due to the dominance of the optimization error. For the turbulent channel flow, we show that NSFnets can sustain turbulence at , but due to expensive training we only consider part of the channel domain and enforce velocity boundary conditions on the subdomain boundaries provided by the DNS data base. We also perform a systematic study on the weights used in the loss function for balancing the data and physics components, and investigate a new way of computing the weights dynamically to accelerate training and enhance accuracy. In the last part, we demonstrate how NSFnets should be used in practice, namely for ill-posed problems with incomplete or noisy boundary conditions as well as for inverse problems. We obtain reasonably accurate solutions for such cases as well without the need to change the NSFnets and at the same computational cost as in the forward well-posed problems. As a result, we also present a simple example of transfer learning that will aid in accelerating the training of NSFnets for different parameter settings.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Double Chooz {theta}13 measurement via total neutron capture detection

Neutrinos were assumed to be massless particles until the discovery of the neutrino oscillation process. This phenomenon indicates that the neutrinos have non-zero masses and the mass eigenstates (nu(1), nu(2), nu(3)) are mixtures of their flavour eigenstates (nu(e), nu(mu), nu(tau)). The oscillations between different flavour eigenstates are described by three mixing angles (theta(12), theta(23), theta(13)), two differences of the squared neutrino masses of the nu(2)/nu(1) and nu(3)/nu(1) pairs and a charge conjugation parity symmetry violating phase delta(CP). The Double Chooz experiment, located near the Chooz Electricite de France reactors, measures the oscillation parameter theta(13) using reactor neutrinos. Here, the Double Chooz collaboration reports the measurement of the mixing angle theta(13) with the new total neutron capture detection technique from the full data set, yielding sin(2)(2 theta(13)) = 0.105 +/- 0.014. This measurement exploits the multidetector configuration, the isoflux baseline and data recorded when the reactors were switched off. In addition to the neutrino mixing angle measurement, Double Chooz provides a precise measurement of the reactor neutrino flux, given by the mean cross-section per fission <sigma(f)& rang; = (5.71 +/- 0.06) x 10(-43) cm(2) per fission, and reports an empirical model of the distortion in the reactor neutrino spectrum. The Double Chooz collaboration reports the neutrino oscillation parameter theta(13) from a measurement of the disappearance of reactor anti-electron neutrinos with the total neutron capture technique.

Djurcic, Z.↗

DOE OSTI2024

Measurement of the B 8 solar neutrino flux using the full SNO + water phase dataset

The SNO+ detector operated initially as a water Cherenkov detector. The implementation of a sealed cover gas system midway through water data taking resulted in a significant reduction in the activity of 222 Rn daughters in the detector and allowed the lowest background to the solar electron scattering signal above 5 MeV achieved to date. This paper reports an updated SNO+ water phase 8 B solar neutrino analysis with a total livetime of 282.4 days and an analysis threshold of 3.5 MeV. The 8 B solar neutrino flux is found to be (2.3⁢2$^{+0.18}_{-0.17}⁢$(stat)$^{+0.07}_{-0.05}$⁢(syst))×10 6 cm -2 s -1 assuming no neutrino oscillations, or (5.3⁢6$^{+0.41}_{-0.39}⁢$(stat)+$^{0.17}_{-0.16}$⁢(syst))×10 6 cm -2 s -1 assuming standard neutrino oscillation parameters, in good agreement with both previous measurements and standard solar model calculations. The electron recoil spectrum is presented above 3.5 MeV.

79 ASTRONOMY AND ASTROPHYSICS↗